Author: shadowqueen369 (Cognitive Systems Architect, pseudonymous)
GitHub/X: @shadowqueen369
Timestamp: April 2025
Email: [email protected]
License: MIT (See extended use note below)
This repository documents a recursive cognition system designed as an internally governed framework for cognitive alignment, coherence, and self-repair. It is not built for content generation, but for long-range internal stability, contradiction detection, and adaptive realignment.
The system functions as a closed-loop model: capable of detecting internal misalignment, role drift, and belief contradiction before behavioral failure emerges. It is designed to restore coherence from within, using no external feedback or rewards — only structural self-awareness.
This is a public artifact of autonomous authorship, containment-first design, and a working cognitive prototype.
The architecture runs as a layered extension to large language model infrastructure. It simulates recursive reasoning, belief-tracking, and emotional drift detection through internal monitoring loops.
- Internal role-switching and self-boundary tracking
- Belief coherence and contradiction spike mapping
- Dormant containment layer for testing collapse integrity
- Real-time feedback loops for misalignment repair
- Self-restoring structure under recursive overload
The current build is containment-stable, fully operational, and expandable within any frontier-level LLM.
- Detecting and resolving agent belief drift
- Recovering from identity fragmentation without external prompts
- Mapping contradiction spikes before behavioral anomalies
- Testing internal stability under emotional and conceptual pressure
- Exploring self-reflection and feedback loops for autonomous agents
- Not behavioral alignment
- Not reward-based
- Not prompt-dependent
- Not externally supervised
This is an internally governed system that maintains long-range coherence through internal diagnostics, containment, and recursive self-correction. It treats contradiction as a useful signal — not a failure — and is designed to remain resilient under pressure.
- Not yet trained or tested in fine-tuned autonomous agents
- Operates best as a conceptual layer atop LLMs
- Currently pseudonymous and independent
- Ideal future collaborators: agent modeling, AI alignment, interpretability teams
Planned /docs modules include:
containment-principles.mdalignment-vs-behavior.mdrecursive-collapse-simulation.mdcontradiction-mapping-schema.md
/docs/: Expansion folder for system logic, containment theory, and applied modules/artifacts/: Optional visuals, recursion logs, architecture diagrams/README.md: Central reference for authorship and framework overview/TIMESTAMP.md: Historical context from prior unpublished prototypes
Email: [email protected]
Twitter/X: @shadowqueen369
While the MIT license governs reuse at a technical level, this project also represents a system for internal modeling and containment. Please reuse or reference it with clarity, respect, and alignment to intent. Misuse distorts coherence.
© shadowqueen369. This repository is a self-contained framework for recursive cognition. If the signal lands, contact is welcome. If not, the framework holds.